Financial institutions moving data workflows into the cloud may be creating new control problems, even as they solve old access issues. According to LSEG Data & Analytics, governance becomes more important in cloud environments, and firms that treat it as an afterthought risk ending up with cloud infrastructure but none of the cloud advantage.
LSEG Data & Analytics argues that cloud architecture can no longer be judged by flexibility or scale alone. Firms must show control over how data is accessed, used, monitored and protected, while also meeting expectations on data sovereignty, operational resilience, auditability and regulatory reporting. The real test is whether a cloud setup creates a trusted operating model.
The problem is that accessibility without control breeds complexity. As more teams consume data, more workflows rely on automated access and more analytical use cases emerge at speed, the absence of a clear governance model can make that flexibility hard to manage. For pricing and reference data, which feed trading, portfolio management, risk, compliance, operations and reporting, the stakes are especially high.
Historically, governance was applied after data had been delivered, moved or transformed. LSEG Data & Analytics notes that this approach struggles in distributed environments where data flows across many platforms and teams. Security, lineage, access management and operational monitoring now need to be foundational rather than an overlay added later.
Crucially, the cloud does not simplify governance by default. If firms replicate file-based delivery, duplicated storage and fragmented transformation processes in the cloud, they carry legacy control problems with them, it said. Data may still need reconciling across environments, access may still be managed inconsistently and lineage may still depend on manual documentation.
LSEG Data & Analytics positions compliance by design as the answer, treating control as part of the architecture itself. Its DataScope Warehouse offers direct cloud access to pricing and reference data, which can be queried using SQL within Snowflake and Google BigQuery, with Databricks availability coming soon. By reducing file movement, staging and duplicated infrastructure, direct query models mean fewer handoffs where controls, lineage and access logic could break down.
Strong governance, however, should not make data unusable. The challenge is building controls without slowing analytics, reporting and AI initiatives. The balance, according to LSEG Data & Analytics, is data that is easier to query and integrate, yet still managed with clarity around permissions, lineage and usage.
Resilience is also now part of the trust equation. It is not only about uptime but about an organisation’s ability to maintain control, explain data use and keep critical workflows running during disruption, particularly as decision windows shrink and regulatory expectations evolve.
Ultimately, LSEG Data & Analytics frames compliance by design as a strategic foundation rather than a regulatory box to tick. The firms that succeed, it suggests, will see compliance not as a brake on innovation, but as one of the conditions that makes innovation safe to scale.
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